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High-resolution imaging of the excised porcine heart at a whole-body 7 T MRI system using an 8Tx/16Rx pTx coil.

Magma (New York, N.Y.)
INTRODUCTION: MRI of excised hearts at ultra-high field strengths ([Formula: see text]≥7 T) can provide high-resolution, high-fidelity ground truth data for biomedical studies, imaging science, and artificial intelligence. In this study, we demonstra...

Dose reduction and image enhancement in micro-CT using deep learning.

Medical physics
BACKGROUND: In preclinical settings, micro-computed tomography (CT) provides a powerful tool to acquire high resolution anatomical images of rodents and offers the advantage to in vivo non-invasively assess disease progression and therapy efficacy. M...

Synthetic CT generation from CBCT using double-chain-CycleGAN.

Computers in biology and medicine
PURPOSE: Cone-beam CT (CBCT) has the advantage of being less expensive, lower radiation dose, less harm to patients, and higher spatial resolution. However, noticeable noise and defects, such as bone and metal artifacts, limit its clinical applicatio...

MLF-IOSC: Multi-Level Fusion Network With Independent Operation Search Cell for Low-Dose CT Denoising.

IEEE transactions on medical imaging
Computed tomography (CT) is widely used in clinical medicine, and low-dose CT (LDCT) has become popular to reduce potential patient harm during CT acquisition. However, LDCT aggravates the problem of noise and artifacts in CT images, increasing diagn...

Deep learning-enabled segmentation of ambiguous bioimages with deepflash2.

Nature communications
Bioimages frequently exhibit low signal-to-noise ratios due to experimental conditions, specimen characteristics, and imaging trade-offs. Reliable segmentation of such ambiguous images is difficult and laborious. Here we introduce deepflash2, a deep ...

Application of synthetic data in the training of artificial intelligence for automated quality assurance in magnetic resonance imaging.

Medical physics
BACKGROUND: Magnetic resonance imaging scanner faults can be missed during routine quality assurance (QA) if they are subtle, intermittent, or the test being performed is insensitive to the type of fault. Coil element malfunction is a common fault wi...

Comparison of deep learning-based reconstruction of PROPELLER Shoulder MRI with conventional reconstruction.

Skeletal radiology
OBJECTIVE: To compare the image quality and agreement among conventional and accelerated periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI with both conventional reconstruction (CR) and deep learning-based r...

A deep learning-based framework for retinal fundus image enhancement.

PloS one
PROBLEM: Low-quality fundus images with complex degredation can cause costly re-examinations of patients or inaccurate clinical diagnosis.

CTformer: convolution-free Token2Token dilated vision transformer for low-dose CT denoising.

Physics in medicine and biology
. Low-dose computed tomography (LDCT) denoising is an important problem in CT research. Compared to the normal dose CT, LDCT images are subjected to severe noise and artifacts. Recently in many studies, vision transformers have shown superior feature...

Unpaired low-dose computed tomography image denoising using a progressive cyclical convolutional neural network.

Medical physics
BACKGROUND: Reducing the radiation dose from computed tomography (CT) can significantly reduce the radiation risk to patients. However, low-dose CT (LDCT) suffers from severe and complex noise interference that affects subsequent diagnosis and analys...